In a long term project with investigators from the Nervous System Development and Plasticity Section, NICHD, and the Program on Pediatric Imaging and Tissue Sciences (PPITS), NICHD we study the dynamic regulation of myelin by the surrounding glial cells and show that it is dependent on the level of activity present in an axon. We elucidated the biological mechanisms by which astrocytes regulate this process and use a theoretical framework to predict how the changes in myelin thickness, as well as the increase in the nodal width, affects the propagation of the signals along a myelinated axon, and to experimentally measure conduction speeds using a data analysis framework we implemented. The theoretical and experimental results were in a very good agreement. A manuscript describing these methods and ultimately the mechanism of the dynamic myelin regulation is in the final phases of revision in the Proceedings of the National Academy of Sciences. We also developed different models of myelin plasticity, or generally, delay plasticity in which we show how the stability of the synchronized state in the network, as well as general stability of the system, relies on having such adaptive delay. The consequences of such adaptive time delays are studied for three main cases: a) where the plasticity is activity-dependent; b) where the plasticity depends on the time arrivals of the postsynaptic and presynaptic action potentials; and c) where the plasticity depends on the oligodendrocytes myelinated multiple axons. For (a), we studied the effect of activity-dependent adaptive time delays on the stability of the system of coupled oscillators, with its implications on the stability of the oscillations and synchrony in the brain, while b) and c) are studied in terms of synchronization in the spiking neural networks. A manuscript describing this work is in preparation. In a project with investigators of the Section on Behavioral Neurogenetics in the Intramural Research Program at NICHD, we study patterns of gene expression in developing zebrafish using supervised and unsupervised machine learning methods and develop a framework for automated annotation of the zebrafish brain neuroanatomy. This work will allow the production of maps with increasingly fine-grained segmentation of distinct neuronal cell types and has been published in the journal Methods in the spring of 2018. Together with several other principal investigators from NIH (NICHD, NINDS, and NIMH), we continue research under the recently obtained R24 BRAIN Initiative grant (In Vivo Brain Network Latency Mapping). The goal of this effort is to measure the temporal latencies (i.e., the time delays) in a human brain signaling between different regions. Being able to measure the latency information in vivo can provide a great diagnostic tool for a number of neuropsychiatric disorders. Our experimental protocol consists of four different imaging modalities: diffusion MRI, providing the structural information, electroencephalography (EEG), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS) which provides dynamic and functional information. One of the results is the development of the algorithms for extracting latency information from the time series data and this work is to be presented at the Annual Meeting of the Society for Neuroscience in San Diego, CA, in November of 2018.